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We received a total of 63 applications (+4 only transcript no application)



Wemade offers to about 26 students=> Final 15

students (5 Women, 10

Men)

Ethnicity:

Caucasian : 7

African:

2

Asian :

4

Hispanic:

1

Multi-Racial: 1

Descriptions of Projects:

A total of eighteen projects were available for the participants to select.

1. Towers of Hanoi (Professor Ernst L. Leiss)

Description: The Towers of Hanoi is a problem that has been well studied and frequentlygeneralized. We are interested in the generalization to arbitrary directed graphs andstudy how many moves in a given graph are necessary to move n disks from the startingpeg to the destination peg. There are known upper and lower bounds on the minimalnumber of moves. The project involves designing algorithms and implementing them forsolving the problem on a given graph and looking at improving the known upper andlower bounds. In particular, parallel moves are of interest.

Objective:

Study recursion using the Towers of Hanoi problem and explore means ofimproving existing bounds. Students will learn implementation and analysis techniques.

Description: Inference control in statistical databases is intimately related to thepreservation of privacy of data stored in such databases. It has proven to be quitedifficult to prevent inferring information about individuals from responses to legitimatestatistical queries. One of the few successful methods involves adding randomly selectedelements to the query set. We want to study experimentally whether removing one ormore elements from the query set achieves similar outcomes. This project extends priorwork for averages to selector functions, in particular medians. The work will involvedetermining how to quantify inference control and how to simulate methods formeasuring it.

Objective: Study the problems of securing statistical databases. Students will learn howto analyze security questions in statistical databases and how to carry out large-scalesimulations.

3.

Digital Watermarks (Professor Ernst L. Leiss)

Description: Watermarks have attractedincreased attention as concerns aboutestablishing ownership of digital media have escalated. Robust invisible watermarksallow one to attach an indelible stamp of ownership; clearly the methods employed mustbe impervious to operations such as rescaling,filtering, or superimposing an additionalwatermark. Robustness is related to the redundancy of the watermark (e. g., if a certainsmall pattern is repeated many times in a watermark, the removal of the watermarkthrough cropping an image is foiled). Similarly, the invisibility of a watermark is relatedto the extent of changes in the information that makes up

the media. This imposes limitson the amount of information that can be encoded in the watermark. The primaryemphasis of the research is on verification techniques.

Objective: Study digital watermarking algorithms and determine their properties.Students will learn about aspects of digital watermarks.

Algorithm analysis is a well-studied discipline, as is software development.However, at the

interface between these two disciplines much can and does go wrong. Infact, many programmers have experienced situations where a good algorithm (that is,correct and efficient) resulted in either wrong or unacceptably slow software. The causesof the differences between the behaviors of algorithms and software can be categorizedinto several areas, namely the implications of the non-uniform memory in realarchitectures (both caches and virtual

memory management are implicated), systemissues (memory mappings, passing of parameters, garbage collection, and optimizationtechniques are important here), implicit assumptions (including exception handling),and the finiteness of thenumber representation (which does not only have relevance fornumerical applications, but is also important if one tests for equality or assumesmathematical identities hold).

software. Students will learn how to obtain good software fromalgorithms.

5. Put it on the Cloud (Professor Ioannis Pavlidis)

Description: In this project the student will work with a team of Research AssistantProfessors and Ph.D. students to design and implement the migration of massiveamounts of research data on the cloud. These data have been collected as part of an NSFproject the last three years and need to be made available to the research community atlarge. Putting massive amounts of research data on the cloud for communal use is a cleartrend and is projected to grow by leaps and bounds, becoming an R&D field and businessall by itself. Migration of such data sets is a complex operation and involves issues oforganizational design, data checking and integrity, user interfacing, as well as datamining and annotation. The student will learn and use XNAT and Azure among othercutting edge tools.

6. Total Mobility (Professor Ioannis Pavlidis)

Description: In this projectthe student will work with a Research Assistant Professor todevelop algorithmic software that differentiates various patterns of physical activity fromiPhone accelerometer data. These anonymous data are collected by free experimentalapplications that the Computational Physiology Lab has released in the App Store thelast couple of years and are used by thousands of people around the world. The ultimategoal is to automatically understand when someone walks versus when s/he runs versuswhen s/he climbs the stairs versus when s/he bikes. Such capability has tremendousvalue in total health management applications as well as in gathering detailedanthropological statistics of mobility at a global scale. The next “Fittest Cities in America”list may well be decided by the software that you will develop in this project!

7. Local and Global Relationship in Face Recognition (Professor IoannisKakadiaris and Shishir Shah)

Description:

Automatic image analysis and computer vision techniques have beendeveloped forface recognition. Nonetheless, the ability to replicate a human＊s ability torecognize a face has not yet been surpassed. To this extent, it is critical to understand theperceptual and reasoning power of humans. One of the questions that remainunanswered

is that of the role of partial observations in recognizing a face. In this project,a student will learn to design an experiment to assess human recognition ability in wholeand partially observed images. The student will develop a web-based platform forimagetagging and combine it with a crowd-sourcing platform such as Amazon MechanicalTurk.

Specific Requirements:

We are looking for a skillful and creative individual, familiar withweb development technologies and database applications.

8. 3D Model of

my Face (Professor Ioannis Kakadiaris and Shishir Shah)

Description: Computer Vision technologies have been starting to emerge inentertainment platforms and remotely controlled-interfaces using affordable imagingsensors and devices like Microsoft＊s Kinect. RGB-D cameras such as those used inKinect capture image (RGB) and depth (D) data, using a range camera and IR light, andallow for 2D and 3D image data acquisition. Such data can be used for 3D scenereconstruction, target location and tracking. In this project, a student will use the Kinectsensor to capture faces and develop methods to reconstruct 3D models. The student willlearn to use open-source drivers and software to facilitate data capture and analysis.

Specific Requirements:

We are looking for a creative individual knowledgeable on one ormore of the following fields: Open-source Software, Computer Vision, ComputerGraphics, Computer Games & Animation, Data Visualization.

Description: Every year 1.4 million Americans suffer a heart attack; in 2004, over800,000 of these attacks were fatal. Large amounts of diverse data points are typicallymeasured while screening individuals during routine health checkups and diagnosis.

Incollaboration with cardiologists and computational scientists, a student will learnfundamentals of machine learning and evaluate methods that can assess the value ofcollected data points for the design of a system to identify individuals at risk of having aheart attack.

Specific Requirements: We are looking for a driven and dynamic individual.

10. Stepping-stone Intrusion Detection (Professor Stephen Huang)

Description: In order to avoid being detected, computer hackers typically go through alongchain of computers to break into a target machine. This can be achieved by using achain of stepping-stones hosts or through Tor. We are interested in real-time algorithmsthat can detect such intruders effectively. The project involves the integration ofalgorithm design, network protocol, and computer security techniques into a system.

Specific Requirements: We are seeking students with some programming experience inC/C++ or Java, knowledge of OS or computer networks a plus. Students with experienceusing Tor (a network of virtual tunnels) are a plus.

has been an important technique in hematology, and it canbe used to detect and identify the minor cell population from bone marrow or blood.Most of the current studies are still based on manual gating by medical scientist andresearchers. This process is not only labor intensive, but also may mislays some potentialcells in other dimensions. We are working on a framework to visualize and analyze theflow cytometry readouts. The result can provide doctors and physicians usefulinformation to diagnose blood or lymphatic diseases, such as Leukemia, Myeloma, andLymphoma. We are seeking students with interest in data mining and/or machinelearning.

Specific Requirements: We are seeking students with data mining and/or Matlab skills tohelp us analyze the data.

12. Information Extraction and Text Mining (Professor Rakesh Verma)

Description: We are looking for enthusiastic, passionate and bright students for all ourprojects. This project will investigate how to extract the most relevant information fromtext

documents and construct a summary and how to evaluate the quality of theinformation extracted.

We are looking for enthusiastic, passionate and bright students for all ourprojects. This project involves the design andimplementation of natural languageprocessing and machine learning techniques for problems in counterterrorism andcomputer security.

Specific Requirements: Some knowledge of Perl or Weka is desirable.

Objective: Student will learn NLP and text mining techniques.

14.

NLP techniques for Lies and Fraud Detection (Professor Rakesh Verma)

Description: We are looking for enthusiastic, passionate and bright students for all ourprojects. This project involves the design and implementation of natural languageprocessing techniques for detection of fraudulent reviews and financial documents.

Specific Requirements: Some knowledge of Perl is desirable but not required.

Objective: Student will learn NLP and text mining techniques.

15.

Computer Security (Professor Rakesh Verma)

Description: We are looking for enthusiastic, passionate and bright students for all ourprojects. This project involves the study and analysis of how man-in-the-middle attackscan be prevented in cryptographic protocols.

Specific Requirements: Interest in formal methods.

Objective: Explore assumptions of different computing paradigms and determine howtheir differences affect software. Students will learn how to obtain good software fromalgorithms.

16. Wireless Sensor Networks (Professor Rakesh Verma)

Description: We are looking for enthusiastic, passionate and bright students for all ourprojects. This project involves the design and analysis of protocols for wireless sensornetworks.

Objective: Wireless sensor networks in general and wireless sensor security in particular.

project is to convert idle PCs into a virtualcluster for executing parallel applications. The project has developed VolpexMPI, afailure resistant MPI (Message Passing Interface) library designed to execute scientificapplications. Volpex software is integrated with BOINC (Berkeley Open Infrastructurefor Network Computing) and deployed to build a volunteer PC pool around the world.The objective of this student project is to measure and evaluate the performance andscalability of selected applications executing on 100s to 1000s of nodes around the worldunder Volpex/BOINC control.

Specific Requirements: The project will involve socket programming and C programming.Knowledge of parallel computing is desirable.

18. Accelerated Review of Video Lectures (Professor Jaspal Subhlok)

Description: Video of classroom lectures is often made available as additional material toa conventional course, as the core of distance learning coursework,or posted publicly forcommunity learning or as reference material. Priorresearch has established thatrecorded Tablet PC lectures are a powerful resource on par with a textbook andclassroom experience. At the same time, a major weakness of the video format is theinability to quickly access the content of interest. In this project, a student will developmethods to automatically identify index points in recorded lecture videos as a means toprovide content-based access to a subject matter.The student will learn fundamentals ofvideo and image analysis and learn to model spatio-temporal signals for quantitativeunderstanding of information content.